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» A Markov chain sequence generator for power macromodeling
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CVPR
2007
IEEE
14 years 9 months ago
Compositional Boosting for Computing Hierarchical Image Structures
In this paper, we present a compositional boosting algorithm for detecting and recognizing 17 common image structures in low-middle level vision tasks. These structures, called &q...
Tianfu Wu, Gui-Song Xia, Song Chun Zhu
SFM
2007
Springer
14 years 1 months ago
Tackling Large State Spaces in Performance Modelling
Stochastic performance models provide a powerful way of capturing and analysing the behaviour of complex concurrent systems. Traditionally, performance measures for these models ar...
William J. Knottenbelt, Jeremy T. Bradley
ICASSP
2010
IEEE
13 years 8 months ago
Phone recognition using Restricted Boltzmann Machines
For decades, Hidden Markov Models (HMMs) have been the state-of-the-art technique for acoustic modeling despite their unrealistic independence assumptions and the very limited rep...
Abdel-rahman Mohamed, Geoffrey E. Hinton
ECCV
2008
Springer
15 years 8 days ago
Co-Recognition of Image Pairs by Data-Driven Monte Carlo Image Exploration
We introduce a new concept of co-recognition for object-level image matching between an arbitrary image pair. Our method augments putative local regionmatches to reliable object-...
Minsu Cho (Seoul National University), Young Min S...
AI
2006
Springer
13 years 7 months ago
Backward-chaining evolutionary algorithms
Starting from some simple observations on a popular selection method in Evolutionary Algorithms (EAs)--tournament selection--we highlight a previously-unknown source of inefficien...
Riccardo Poli, William B. Langdon